A Comparative Study of Unbalanced Production Lines Using Simulation Modeling: A Case Study for Solar Silicon Manufacturing

In the solar silicon manufacturing industry, the production time for crystal growth is ten times longer than at other workstations. The pre-processing time at the ingot-cutting station causes work-in-process (WIP) accumulation and an excessively long cycle time. This study aimed to find the most effective production system for reducing WIP accumulation and shortening the cycle time. The proposed approach considered pull production systems, and the response surface methodology was adopted for performance optimization. A simulation-based optimization technique was used for determining the optimal pull production system. The comparison between the results of various simulated pull production systems and those of the existing solar silicon manufacturing system showed that a hybrid production system in which a kanban station was installed before the bottleneck station with a CONWIP system incorporated for the rest of the production line could reduce the WIP volume by 26% and shorten the cycle time by 16% under the same throughput conditions.

Evaluation of Pull Production Control Mechanisms by Simulation

Today, companies need to continuously improve their production processes, which is a complex task. Lean manufacturing is one of the methodologies for production improvement, and one of the basic goals of any lean implementation is to reduce work-in-process (WIP) and shorten the production lead time. One of the basic lean principles for achieving these goals is pull principle. The adoption of this principle is quite challenging, as it requires a long-term commitment in the application and adoption of various lean techniques and tools that are prerequisites for the successful introduction of the pull principle. Kanban is the most well-known pull production control mechanism, and the first one developed within Toyota production system, but later, other pull control mechanisms were developed. Some of them include Conwip, Hybrid Kanban/Conwip, and Drum Buffer Rope (DBR), and those three, together with Kanban, were the research topic of this study. These four mechanisms were not explored and compared all together not for these specific production configurations considered in this research but also with regard to optimal parameters of control mechanisms. The goal was to analyze and compare how these pull control mechanisms affect lead time in different production conditions. For this purpose, simulation experiments were performed. The results showed that for different production conditions, different pull control mechanisms are optimal in terms of shortening lead time. This finding could help companies as a guideline for making a decision in terms of which pull control mechanism to choose.

System dynamics modelling of fixed and dynamic Kanban controlled production systems: a supply chain perspective

Purpose Pull production systems have received much attention in the supply chain management environment. The number of Kanbans is a key decision variable in the pull production system as it affects the finished goods inventory (FGI) and backorders of the system. The purpose of this study is to compare the performance of the fixed and dynamic Kanban systems in terms of operational metrics (FGI and backorders) under the demand uncertainty. Design/methodology/approach In this paper, the system dynamics (SD) approach was used to model the performance of fixed and dynamic Kanban based production systems. SD approach has enabled the feedback mechanism and is an appropriate tool to incorporate the dynamic control during the simulation. Initially, a simple Kanban based production system was developed and then compared the performance of production systems with fixed and dynamic controlled Kanbans at the various demand scenarios. Findings From the present study, it is observed that the dynamic Kanban system has advantages over the fixed Kanban system and also observed that the variation in the backorders with respect to the demand uncertainty under the dynamic Kanban system is negligible. Research limitations/implications In a just-in-time production system, the number of Kanbans is a key decision variable. The number of Kanbans is mainly depended on the demand, cycle time, safety stock factor (SSF) and container size. However, this study considered only demand uncertainty to compare the fixed and dynamic Kanban systems. This paper further recommends researchers to consider other control variables which may influence the number of Kanbans such as cycle time, SSF and container size. Originality/value This study will be useful to decision-makers and production managers in the selection of the Kanban systems in uncertain demand applications.

Kanban Systems in the Context of the Enterprise Systems

Companies are under increasing pressure from customers, competitors, limited resources, etc. These conditions oblige companies to permanently improve their organizational structure and the activities of all system’s flows. The paper analyses the types of Kanban systems, in the broader context of the enterprise systems. The most important reference architectures were analysed (with the emphasis on the modules dedicated to flow description) and the standards that allow the activity modelling of a manufacturing enterprises. Starting from this context, the paper describes three models of Kanban systems that are specific to companies with different information systems development. Models are: Push production with withdrawal Kanban; Pull production with withdrawal Kanban and production Kanban triggered by Kanban board; Pull production with withdrawal Kanban and production Kanban triggered by the dispatch to the customers. The models are graphically described using Value Stream Map (VMS) symbols. These models are useful in the development and improvement of production flows.

Pull Production Systems

This chapter aims to organize knowledge about pull production systems by presenting the underlying concepts of lean manufacturing as for its origin, principles, and relations with PPC. Pull production is one the fundamental principles of lean manufacturing, and its implementation can bring positive impacts. For such a purpose, sequential and mixed supermarket pull systems stand out in which the integration between pull production systems and PPC and its various levels is a main subject of discussion. The JIT model or Kanban method and hybrid systems, such as conwip and lung-drum-string theory, are mechanisms for managing pull production systems. Finally, a pull production system implementation is presented for illustration purposes. At the end of this chapter, it is expected that skills are developed by readers, which are going to assist them in using the tools presented to model production systems and aid decision-making processes.

Model for planning and controlling the delivery and assembly of engineer-to-order prefabricated building systems: exploring synergies between Lean and BIM

The adoption of prefabricated building systems has grown due to the need to reduce duration and cost of construction projects, as well as to improve quality and working conditions. However, the adoption of those systems requires an intense exchange of information to integrate the production of components, logistics operations, and site assembly. This is particularly important in engineer-to-order environments, in which the level of uncertainty tends to be high. This research proposes a model for planning and controlling the delivery and assembly of ETO prefabricated building systems, emphasizing the integration between site installation and logistics operations. This model was devised in an empirical study carried out in a company that delivers and assembles prefabricated concrete structures. The main theoretical contribution is a set of approaches to implement the “pull production” and “reduce variability” principles in this particular context, exploring synergies that exist between Lean Production principles and Building Information Modeling (BIM) functionalities.